# %run test_dataset

[320, 214] [46, 214]
[501, 241] [295, 241]
[464, 232] [195, 232]
[313, 204] [148, 204]

%run train

self.device is cuda:0
132
Epoch: 0, Itration: 0
loss_G_GAN = 9.762478828430176, loss_G_L1 = 0.5613824129104614 * 10.0
loss_D = 0.7322220206260681

Epoch: 33, Itration: 1000
loss_G_GAN = 6.123374938964844, loss_G_L1 = 0.2800010144710541 * 10.0
loss_D = 0.04401622340083122

Epoch: 66, Itration: 2000
loss_G_GAN = 5.911088943481445, loss_G_L1 = 0.21833613514900208 * 10.0
loss_D = 0.05884137004613876

Epoch: 100, Itration: 3000
loss_G_GAN = 2.849618434906006, loss_G_L1 = 0.22880354523658752 * 10.0
loss_D = 0.2758593261241913

Epoch: 133, Itration: 4000
loss_G_GAN = 3.2131428718566895, loss_G_L1 = 0.30421608686447144 * 10.0
loss_D = 0.1478511542081833

Epoch: 166, Itration: 5000
loss_G_GAN = 4.426914215087891, loss_G_L1 = 0.22197002172470093 * 10.0
loss_D = 0.6342664957046509

Epoch: 200, Itration: 6000
loss_G_GAN = 0.9416372179985046, loss_G_L1 = 0.22713330388069153 * 10.0
loss_D = 0.5406668186187744

Epoch: 233, Itration: 7000
loss_G_GAN = 1.7029156684875488, loss_G_L1 = 0.3121352791786194 * 10.0
loss_D = 0.3730054497718811

Epoch: 266, Itration: 8000
loss_G_GAN = 2.2681503295898438, loss_G_L1 = 0.21589334309101105 * 10.0
loss_D = 0.3615301251411438

Epoch: 300, Itration: 9000
loss_G_GAN = 0.7081899642944336, loss_G_L1 = 0.21542367339134216 * 10.0
loss_D = 0.6335645914077759

Epoch: 333, Itration: 10000
loss_G_GAN = 1.4917635917663574, loss_G_L1 = 0.3139137029647827 * 10.0
loss_D = 0.3876226246356964

Epoch: 366, Itration: 11000
loss_G_GAN = 1.9171944856643677, loss_G_L1 = 0.21581986546516418 * 10.0
loss_D = 0.2821212410926819

Epoch: 400, Itration: 12000
loss_G_GAN = 1.496167540550232, loss_G_L1 = 0.21874302625656128 * 10.0
loss_D = 0.5973381996154785

Epoch: 433, Itration: 13000
loss_G_GAN = 1.8126041889190674, loss_G_L1 = 0.3119634985923767 * 10.0
loss_D = 0.215749591588974

Epoch: 466, Itration: 14000
loss_G_GAN = 1.6787595748901367, loss_G_L1 = 0.2090642899274826 * 10.0
loss_D = 0.20427551865577698

save model to ./checkpoints/pix2food.pkl



 # --- Validation Set --- # 

import numpy as np
import cv2 as cv
from matplotlib import pyplot as plt

img = cv.imread('home.png')
hsv = cv.cvtColor(img,cv.COLOR_BGR2HSV)
hist = cv.calcHist([hsv], [0, 1], None, [180, 256], [0, 180, 0, 256] )
plt.imshow(hist,interpolation = 'nearest')
plt.show()